---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-42-466164d09c52> in <module>()
     47                         batch_size=256,
     48                         max_mc_iter=100,
---> 49                         num_target_bit_errors=1000)   #num_target_bit_errors =1000
     50 
     51     print(type(ber))

<ipython-input-41-c54316f97a78> in sim_ber_test(mc_fun, ebno_dbs, batch_size, max_mc_iter, soft_estimates, num_target_bit_errors, num_target_block_errors, early_stop, verbose, forward_keyboard_interrupt, dtype)
    211                 iter_count += 1
    212 
--> 213                 outputs,x = mc_fun(batch_size=batch_size, ebno_db=ebno_dbs[i])
    214 
    215                 # assume first and second return value is b and b_hat

D:\anaconda_main\lib\site-packages\keras\engine\base_layer.py in __call__(self, *args, **kwargs)
   1035         with autocast_variable.enable_auto_cast_variables(
   1036             self._compute_dtype_object):
-> 1037           outputs = call_fn(inputs, *args, **kwargs)
   1038 
   1039         if self._activity_regularizer:

D:\anaconda_main\lib\site-packages\tensorflow\python\eager\def_function.py in __call__(self, *args, **kwds)
    883 
    884       with OptionalXlaContext(self._jit_compile):
--> 885         result = self._call(*args, **kwds)
    886 
    887       new_tracing_count = self.experimental_get_tracing_count()

D:\anaconda_main\lib\site-packages\tensorflow\python\eager\def_function.py in _call(self, *args, **kwds)
    931       # This is the first call of __call__, so we have to initialize.
    932       initializers = []
--> 933       self._initialize(args, kwds, add_initializers_to=initializers)
    934     finally:
    935       # At this point we know that the initialization is complete (or less

D:\anaconda_main\lib\site-packages\tensorflow\python\eager\def_function.py in _initialize(self, args, kwds, add_initializers_to)
    758     self._concrete_stateful_fn = (
    759         self._stateful_fn._get_concrete_function_internal_garbage_collected(  # pylint: disable=protected-access
--> 760             *args, **kwds))
    761 
    762     def invalid_creator_scope(*unused_args, **unused_kwds):

D:\anaconda_main\lib\site-packages\tensorflow\python\eager\function.py in _get_concrete_function_internal_garbage_collected(self, *args, **kwargs)
   3064       args, kwargs = None, None
   3065     with self._lock:
-> 3066       graph_function, _ = self._maybe_define_function(args, kwargs)
   3067     return graph_function
   3068 

D:\anaconda_main\lib\site-packages\tensorflow\python\eager\function.py in _maybe_define_function(self, args, kwargs)
   3461 
   3462           self._function_cache.missed.add(call_context_key)
-> 3463           graph_function = self._create_graph_function(args, kwargs)
   3464           self._function_cache.primary[cache_key] = graph_function
   3465 

D:\anaconda_main\lib\site-packages\tensorflow\python\eager\function.py in _create_graph_function(self, args, kwargs, override_flat_arg_shapes)
   3306             arg_names=arg_names,
   3307             override_flat_arg_shapes=override_flat_arg_shapes,
-> 3308             capture_by_value=self._capture_by_value),
   3309         self._function_attributes,
   3310         function_spec=self.function_spec,

D:\anaconda_main\lib\site-packages\tensorflow\python\framework\func_graph.py in func_graph_from_py_func(name, python_func, args, kwargs, signature, func_graph, autograph, autograph_options, add_control_dependencies, arg_names, op_return_value, collections, capture_by_value, override_flat_arg_shapes, acd_record_initial_resource_uses)
   1005         _, original_func = tf_decorator.unwrap(python_func)
   1006 
-> 1007       func_outputs = python_func(*func_args, **func_kwargs)
   1008 
   1009       # invariant: `func_outputs` contains only Tensors, CompositeTensors,

D:\anaconda_main\lib\site-packages\tensorflow\python\eager\def_function.py in wrapped_fn(*args, **kwds)
    666         # the function a weak reference to itself to avoid a reference cycle.
    667         with OptionalXlaContext(compile_with_xla):
--> 668           out = weak_wrapped_fn().__wrapped__(*args, **kwds)
    669         return out
    670 

D:\anaconda_main\lib\site-packages\tensorflow\python\eager\function.py in bound_method_wrapper(*args, **kwargs)
   3988     # However, the replacer is still responsible for attaching self properly.
   3989     # TODO(mdan): Is it possible to do it here instead?
-> 3990     return wrapped_fn(*args, **kwargs)
   3991   weak_bound_method_wrapper = weakref.ref(bound_method_wrapper)
   3992 

D:\anaconda_main\lib\site-packages\tensorflow\python\framework\func_graph.py in wrapper(*args, **kwargs)
    992           except Exception as e:  # pylint:disable=broad-except
    993             if hasattr(e, "ag_error_metadata"):
--> 994               raise e.ag_error_metadata.to_exception(e)
    995             else:
    996               raise

ValueError: in user code:

    <ipython-input-36-e8b0999d2da5>:226 call  *
        x_hat, no_eff = self._lmmse_equ([y, h_hat, err_var, no])
    D:\anaconda_main\lib\site-packages\sionna\ofdm\equalization.py:136 call  *
        err_var_dt = flatten_last_dims(err_var_dt, 2)
    D:\anaconda_main\lib\site-packages\sionna\utils\tensors.py:110 flatten_last_dims  *
        last_dim = tf.reduce_prod(tensor.shape[-num_dims:])
    D:\anaconda_main\lib\site-packages\tensorflow\python\util\dispatch.py:206 wrapper  **
        return target(*args, **kwargs)
    D:\anaconda_main\lib\site-packages\tensorflow\python\ops\math_ops.py:2744 reduce_prod
        input_tensor, _ReductionDims(input_tensor, axis), keepdims,
    D:\anaconda_main\lib\site-packages\tensorflow\python\ops\math_ops.py:2094 _ReductionDims
        return range(0, array_ops.rank(x))
    D:\anaconda_main\lib\site-packages\tensorflow\python\util\dispatch.py:206 wrapper
        return target(*args, **kwargs)
    D:\anaconda_main\lib\site-packages\tensorflow\python\ops\array_ops.py:839 rank
        return rank_internal(input, name, optimize=True)
    D:\anaconda_main\lib\site-packages\tensorflow\python\ops\array_ops.py:859 rank_internal
        input = ops.convert_to_tensor(input)
    D:\anaconda_main\lib\site-packages\tensorflow\python\profiler\trace.py:163 wrapped
        return func(*args, **kwargs)
    D:\anaconda_main\lib\site-packages\tensorflow\python\framework\ops.py:1566 convert_to_tensor
        ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref)
    D:\anaconda_main\lib\site-packages\tensorflow\python\framework\constant_op.py:363 _tensor_shape_tensor_conversion_function
        "Cannot convert a partially known TensorShape to a Tensor: %s" % s)

    ValueError: Cannot convert a partially known TensorShape to a Tensor: (None, 4)